|
|
Absolute deviation, 绝对离差
3 _+ ?/ V9 Z0 L) s8 vAbsolute number, 绝对数
2 V5 Z' w B% |( S6 R; K g9 ?Absolute residuals, 绝对残差
H+ C5 w ?( E/ xAcceleration array, 加速度立体阵
( n# p5 M( h: ?: w9 r C5 e7 k0 oAcceleration in an arbitrary direction, 任意方向上的加速度
1 X- M- w/ \/ M2 F+ p% Y/ EAcceleration normal, 法向加速度
4 \" o. n* d/ V: A) X& XAcceleration space dimension, 加速度空间的维数: M2 o/ Z. R& U6 @8 E
Acceleration tangential, 切向加速度+ J! {. k- z/ [6 m
Acceleration vector, 加速度向量
' J6 {" o. A4 _7 ]* g8 xAcceptable hypothesis, 可接受假设
: s/ J* N, Z$ W: B4 z+ U& q7 L% FAccumulation, 累积- K- b' U1 h& [/ h0 n
Accuracy, 准确度
7 v6 S" f0 i+ jActual frequency, 实际频数4 B2 I; N$ d% u! O" x2 z8 j9 M
Adaptive estimator, 自适应估计量+ S, @8 h. Q7 @0 G% l! z
Addition, 相加
8 k% ^ [! q) V5 c3 z' dAddition theorem, 加法定理
$ s* C" W: O' K% e, c& JAdditivity, 可加性- e& i! Y: C- i. U/ N
Adjusted rate, 调整率* g2 R7 v9 Y# n* n' O6 x
Adjusted value, 校正值8 n0 v4 L( d) ~* y( v
Admissible error, 容许误差% h R: l. F8 w% w/ w; x& [& e
Aggregation, 聚集性
3 }5 S+ w$ } m0 |* I) D `% [Alternative hypothesis, 备择假设
' X# n" y8 k) w# i k/ ^* P" `Among groups, 组间, }4 ~0 v# H8 B6 T/ b
Amounts, 总量5 n6 K$ N6 Y3 D/ U% {
Analysis of correlation, 相关分析4 g. Q* _8 b. F2 ^+ X* r% `
Analysis of covariance, 协方差分析
C4 }1 e$ ?3 G' b' I/ t' u' EAnalysis of regression, 回归分析/ k& w% O# G2 O5 I4 a) S2 i
Analysis of time series, 时间序列分析% m/ X+ X- x7 T, J0 U8 g
Analysis of variance, 方差分析
7 z/ u/ ^/ l: u# w3 }Angular transformation, 角转换, Y! v/ L2 m/ u: a! D
ANOVA （analysis of variance）, 方差分析
8 B) n$ @0 y1 j4 G$ ~, wANOVA Models, 方差分析模型
# j; x+ D; f4 i% L5 Y3 mArcing, 弧/弧旋
: `0 _/ _, W1 I$ q+ hArcsine transformation, 反正弦变换
0 N# e m& D& p& ZArea under the curve, 曲线面积0 `/ R1 ^4 T! E# c1 w- ~
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
9 a$ l: K6 u' aARIMA, 季节和非季节性单变量模型的极大似然估计
+ ^' C9 v1 F. r0 n* uArithmetic grid paper, 算术格纸
8 d- E0 X/ Y! e% E, eArithmetic mean, 算术平均数, _, @' O0 t0 r. N! l5 ^ }
Arrhenius relation, 艾恩尼斯关系
1 ?9 ]' I( R% Q" IAssessing fit, 拟合的评估
- r" S W/ U& ]6 L f+ ZAssociative laws, 结合律# u# t! v% M1 @# |
Asymmetric distribution, 非对称分布; Y3 R) F( h! E; S, p$ y# N4 w
Asymptotic bias, 渐近偏倚% H2 u4 T! b, m# i0 f T/ W! i) a
Asymptotic efficiency, 渐近效率
: u! w/ |$ a7 w/ K* x. zAsymptotic variance, 渐近方差7 M; D7 y& D# k
Attributable risk, 归因危险度
3 v3 ^7 ^0 u" R' u1 JAttribute data, 属性资料
2 P# g4 \7 p. ]- M2 @) NAttribution, 属性
# P9 O- d8 c7 F' t4 w; A( UAutocorrelation, 自相关, Z- X" U% I+ P( m4 k, y
Autocorrelation of residuals, 残差的自相关2 | R- F( O; J% d- M; j5 r6 l
Average, 平均数
5 {! L" j3 E* B: L. v0 X" QAverage confidence interval length, 平均置信区间长度
) i9 m) T6 M; _% S5 T7 uAverage growth rate, 平均增长率# e6 _' {- X8 j* w g7 F2 v
Bar chart, 条形图8 I. A- \* N1 G6 |1 ~3 S/ `$ L
Bar graph, 条形图5 ?4 e! e( Q* S/ o( {1 ]
Base period, 基期$ L% r, w. ~# U! j( f" _: t7 U, T
Bayes' theorem , Bayes定理
2 e5 `8 F- j# y5 B8 J- jBell-shaped curve, 钟形曲线
7 H) C: G4 ?3 ~( h; e/ mBernoulli distribution, 伯努力分布% L, L9 t* C' l
Best-trim estimator, 最好切尾估计量+ A9 }8 A0 _2 i! h4 ?" q8 S, s
Bias, 偏性
# r, l- N2 ~! V) h2 w0 `Binary logistic regression, 二元逻辑斯蒂回归
& Y: G4 P% L0 r8 ]) B* UBinomial distribution, 二项分布
$ x* k) l5 C; jBisquare, 双平方0 ]5 o/ @/ d5 @1 R
Bivariate Correlate, 二变量相关
) _$ n( W2 z; C0 IBivariate normal distribution, 双变量正态分布4 Q# b& O( ~2 m& c& m/ ^
Bivariate normal population, 双变量正态总体
* t; Y+ R' ]3 f, N( cBiweight interval, 双权区间
; [0 O2 I( b+ l& T$ }$ k" r# KBiweight M-estimator, 双权M估计量
; B" }! f" ^1 PBlock, 区组/配伍组: P9 `0 q+ ?+ h2 c
BMDP(Biomedical computer programs), BMDP统计软件包
+ I- S, k, Z5 D; [7 F Z! qBoxplots, 箱线图/箱尾图; ? ~8 W$ @5 U2 ^; ~, p9 Z
Breakdown bound, 崩溃界/崩溃点" q7 E7 ?' i% e& v& c M1 G, x; o1 a6 P
Canonical correlation, 典型相关4 _' g1 M2 w6 V
Caption, 纵标目
, T C' I. n4 m& l! F8 L6 ICase-control study, 病例对照研究/ M% `# @- B4 W) D% \7 w8 D
Categorical variable, 分类变量+ c) w9 @: u- @8 Z; N0 D
Catenary, 悬链线 }3 w) C U$ u0 k6 q0 a* H2 y* w9 w
Cauchy distribution, 柯西分布
' V5 Q3 ~2 |. J* u* X# gCause-and-effect relationship, 因果关系: t7 N% p6 J# L9 j9 T: w
Cell, 单元
2 X0 j, f$ E. K* r/ K+ |Censoring, 终检
8 j i+ L4 ]8 {- SCenter of symmetry, 对称中心
' F0 t* o% |4 E B3 k2 ICentering and scaling, 中心化和定标3 P9 j# }% ?9 ?) M; P5 x: G' N
Central tendency, 集中趋势- _$ v7 |) K/ @# N# m+ Z
Central value, 中心值
/ p6 c( d" j+ {: _( @5 z* UCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测# G7 S' o4 Q6 S6 o5 n3 d
Chance, 机遇
$ M- H6 O1 x% @! GChance error, 随机误差' ~/ v3 T8 v* W: H
Chance variable, 随机变量
7 M' q' T; x0 E' WCharacteristic equation, 特征方程- H0 Q& {- k5 F2 D$ }7 p
Characteristic root, 特征根& j# y! R1 ~1 b
Characteristic vector, 特征向量; ]6 z- o' G) v) V3 m' d
Chebshev criterion of fit, 拟合的切比雪夫准则
5 z2 L9 R: m4 J8 f' r- `8 vChernoff faces, 切尔诺夫脸谱图
0 g8 [! B2 C, Q5 W/ m0 DChi-square test, 卡方检验/χ2检验
( ]7 e" n# [0 z3 L" t- TCholeskey decomposition, 乔洛斯基分解
5 ]2 V& g, e) [" d- CCircle chart, 圆图
, ~% J1 ~/ z: w" x1 i- h( N% G" oClass interval, 组距
: I) d7 O# l. v: w7 |Class mid-value, 组中值4 t" L }+ {) s2 A
Class upper limit, 组上限
% G9 s8 @& {( t; L4 t4 } r/ bClassified variable, 分类变量7 n3 o' S. F1 j
Cluster analysis, 聚类分析
+ z5 `3 l6 F% L8 wCluster sampling, 整群抽样
5 J G6 _ N# R o. G( VCode, 代码
* A4 ^4 n8 E( L% N. L5 W3 S! b1 N, ~Coded data, 编码数据/ p! f* C$ X7 r1 [6 ^ H0 Q
Coding, 编码# u6 O6 k$ N1 Z7 |% a
Coefficient of contingency, 列联系数
3 Y; d# b) T1 Y) o% ?6 F# X2 U5 nCoefficient of determination, 决定系数
6 \. f8 d2 E+ Y& h8 v% iCoefficient of multiple correlation, 多重相关系数- M& V, a) W( C/ ~% g
Coefficient of partial correlation, 偏相关系数4 E( N8 A8 G: I7 A1 y" v
Coefficient of production-moment correlation, 积差相关系数; l+ W5 m" A* i: K" q6 V
Coefficient of rank correlation, 等级相关系数2 O/ l8 o( O$ J
Coefficient of regression, 回归系数
, j" O. O4 _- U/ C, {5 p. k5 }$ mCoefficient of skewness, 偏度系数
% m8 n( \4 ~' G7 A1 f# A. NCoefficient of variation, 变异系数( m" X) A% w9 L1 b' ~2 X; q
Cohort study, 队列研究
& \6 @! @% a* J8 i3 u( tColumn, 列+ v: F# s. @8 M2 O* U3 A
Column effect, 列效应8 O' `' J) `$ |4 N( u8 s5 c0 o
Column factor, 列因素& @: H; K1 b+ Y. q
Combination pool, 合并! K; b% S$ s- `& q' \ _
Combinative table, 组合表
/ O0 T* `; B6 a5 |Common factor, 共性因子
4 A) q1 C+ M' Y; t' }: KCommon regression coefficient, 公共回归系数, D$ u. T5 F7 T% x* }) _1 M7 G
Common value, 共同值; z$ w' y" S4 D; |% ^: H! d$ T
Common variance, 公共方差" R; R* E! E6 ]: U/ ^
Common variation, 公共变异; g# |! g! i: z6 x
Communality variance, 共性方差! S8 o7 K* H+ g% V' S7 Y
Comparability, 可比性
9 [9 D2 h6 U) o3 e$ |' X5 kComparison of bathes, 批比较) k$ A) e" w. V5 @- t7 O6 q
Comparison value, 比较值2 i2 q, Y3 ^7 H1 p; Y1 L
Compartment model, 分部模型
2 @1 k8 C* n+ n" _- ~' }. D. rCompassion, 伸缩
; Q2 [3 `3 X8 W" ?4 E/ fComplement of an event, 补事件2 j; g3 b& w- E
Complete association, 完全正相关
( e0 O* N6 J1 v9 F3 @9 BComplete dissociation, 完全不相关
* a7 F" x4 b& OComplete statistics, 完备统计量0 Z, M( [. }5 L5 r' O* w3 I7 W8 {1 q
Completely randomized design, 完全随机化设计
# \) \% h6 ~& K6 [% V! oComposite event, 联合事件6 v# R+ @4 g; q+ \4 B/ ?
Composite events, 复合事件
8 v! m" C+ f0 M# u8 j8 HConcavity, 凹性
" y' W! e( R( k$ d' ?9 DConditional expectation, 条件期望6 }+ ^0 x% F, `6 \# f, t
Conditional likelihood, 条件似然* [# [" q1 P) M- V1 y! i
Conditional probability, 条件概率
5 M$ k. _9 k @3 M# O3 d3 yConditionally linear, 依条件线性
. |+ }6 p& U, [6 H/ G0 g }! sConfidence interval, 置信区间
3 x' c+ F h8 eConfidence limit, 置信限
9 o/ j+ K1 K1 k% p. b9 C# N: HConfidence lower limit, 置信下限
' k/ S( j/ G) y; p9 b. vConfidence upper limit, 置信上限% d: R+ U4 g3 V& Q7 h# K
Confirmatory Factor Analysis , 验证性因子分析5 Z0 y* V, d, S" J
Confirmatory research, 证实性实验研究; a4 X+ h7 q: O9 z
Confounding factor, 混杂因素
# \& f p6 ?0 s+ P0 D- e% _" GConjoint, 联合分析
. T& q7 }1 s3 U+ d$ }+ g4 _Consistency, 相合性
7 A5 q' U$ n2 z$ R# y: hConsistency check, 一致性检验9 l% i4 n$ i$ c9 V$ |9 K
Consistent asymptotically normal estimate, 相合渐近正态估计6 Z1 ?* K+ V, B; W. n6 |
Consistent estimate, 相合估计
& f. u* m& D* tConstrained nonlinear regression, 受约束非线性回归
# D3 G8 H7 t9 M8 H; NConstraint, 约束
* Q* v" `$ g- JContaminated distribution, 污染分布% d0 _9 N3 Y" J
Contaminated Gausssian, 污染高斯分布
' X) z8 ]! z- |- w" z9 _* [Contaminated normal distribution, 污染正态分布
! p, u4 S$ q1 R( i7 PContamination, 污染
0 |/ p+ X0 M: Z! z0 Q7 HContamination model, 污染模型
5 Q! Z0 E- y% y3 Z3 ` |+ m# LContingency table, 列联表7 ], j: {3 |- `
Contour, 边界线* U# y# |$ d+ O+ C; K2 T0 Z
Contribution rate, 贡献率) s0 e. x. I$ ?( F# V
Control, 对照4 S) |. z, s. N Z6 |* s% ^9 O
Controlled experiments, 对照实验- U! d0 z' f6 U% c _: L
Conventional depth, 常规深度
8 a0 r3 v% \ K& k: B! W tConvolution, 卷积
! C5 j3 E& S" o* s" O2 RCorrected factor, 校正因子. v- [. {4 B* i W M h
Corrected mean, 校正均值
% J7 N" u3 I- F" Z a4 pCorrection coefficient, 校正系数; R7 d4 W" r) K4 N }2 X' D, f
Correctness, 正确性, W. K; [) k% ^" r
Correlation coefficient, 相关系数
F6 [) i. ^9 |Correlation index, 相关指数
8 C( X4 [. b6 OCorrespondence, 对应
* c0 R: _' b- ]2 ACounting, 计数5 t/ i- n# M% X- K8 Q" h% u' m/ }3 z
Counts, 计数/频数
F* n; N+ \, _9 A/ hCovariance, 协方差
2 g) o8 ~7 J# l! Z' J4 j aCovariant, 共变
9 I, [% r0 q" C3 k% [/ h1 B+ nCox Regression, Cox回归
5 U, d, j _0 B" s& f, Y8 [Criteria for fitting, 拟合准则5 s% x6 D$ x0 c! e
Criteria of least squares, 最小二乘准则* {/ U4 v7 x7 k" k$ [
Critical ratio, 临界比9 J7 C- L; J a5 q
Critical region, 拒绝域
9 T4 t7 E9 \3 m: @1 ^Critical value, 临界值3 |5 D3 R( q( M2 w4 l: S8 q i
Cross-over design, 交叉设计
/ b. f; b* y% ^& q1 r& h% S! Z" FCross-section analysis, 横断面分析( w8 b) S8 p5 E5 K ]
Cross-section survey, 横断面调查: \ F2 U0 a: G9 A( H! S
Crosstabs , 交叉表
0 d* {1 f. j: h1 f- ~$ ?5 [2 |- fCross-tabulation table, 复合表
5 V) \3 s- Q4 i* q* DCube root, 立方根
' f! {9 |) V7 ?! j5 \7 N+ h+ BCumulative distribution function, 分布函数6 y5 A7 L i8 B. K$ P, [# [* B
Cumulative probability, 累计概率
8 | a7 h! ]0 \" GCurvature, 曲率/弯曲
: @9 u9 K) p, KCurvature, 曲率5 }4 E. q) T0 C2 |6 r
Curve fit , 曲线拟和
+ ^) @: Z5 k' o' k dCurve fitting, 曲线拟合
' V( {6 k! K# j$ I# I% ^Curvilinear regression, 曲线回归
2 K! q4 A( Q1 p; G* H5 O: O) QCurvilinear relation, 曲线关系
2 ?6 O7 D; u- i! C7 F' SCut-and-try method, 尝试法- i" e% r0 M# n7 W/ d P
Cycle, 周期4 {3 i0 T% G! T# V/ M
Cyclist, 周期性
2 \ M; E7 A' [( w7 T" ~/ X4 lD test, D检验: [9 I. X1 W3 A. N4 }
Data acquisition, 资料收集2 P& x5 w0 O7 V h. U; s
Data bank, 数据库5 _% [8 g1 A/ }6 j) z" i
Data capacity, 数据容量
1 {) @" h$ p5 y2 b3 z& DData deficiencies, 数据缺乏
/ G3 _& ~# d# @Data handling, 数据处理
/ Y$ J7 W" J4 {! V7 k' R* M$ yData manipulation, 数据处理3 Y6 M, n; }* g' n$ ?1 t m+ r
Data processing, 数据处理
7 U) c" X- Y8 ]Data reduction, 数据缩减
# R8 i" l# U5 n W, VData set, 数据集( d4 U9 d+ h3 E! w4 O$ ?$ ^
Data sources, 数据来源
! m+ H+ E& I4 W1 m$ SData transformation, 数据变换
) r& \9 b# i) N m# g" L( BData validity, 数据有效性: [9 q' M; @- _/ A) h4 s
Data-in, 数据输入, _. k: f+ A7 q3 u/ e4 W& j
Data-out, 数据输出6 K5 U( Z& z! N* V% S
Dead time, 停滞期
6 Y8 S' x& S# H; ODegree of freedom, 自由度( Q2 y8 Y5 @" _ f$ y) R
Degree of precision, 精密度
7 w& p2 g# ^+ k! [: Y5 T2 mDegree of reliability, 可靠性程度
3 ]. a) n, e4 R' b% RDegression, 递减
* g" m8 Z( O" PDensity function, 密度函数
5 v% r% C8 ^5 u* LDensity of data points, 数据点的密度
, Y- W2 g7 P: C: |, i( A% wDependent variable, 应变量/依变量/因变量
0 y- v9 G1 r9 z- i' v" Q1 S1 FDependent variable, 因变量/ G5 t R8 D+ x5 ? [. T
Depth, 深度! T2 q* A; K" S: n" C- T9 F
Derivative matrix, 导数矩阵
6 W5 `% G1 O d: `Derivative-free methods, 无导数方法
+ B1 ~+ m u# @0 G, Q4 XDesign, 设计
. Q( ~: x5 G# _" i: _! g/ uDeterminacy, 确定性$ E: B' W5 N; [' G
Determinant, 行列式0 o; x' ^2 |6 I/ f" o7 ]1 t
Determinant, 决定因素6 B3 Y! n, L0 ~5 R
Deviation, 离差) t0 V7 @& G/ x; l
Deviation from average, 离均差
2 A( ~1 C; u- ]7 v! k8 pDiagnostic plot, 诊断图5 o7 @* q- o( ~; g5 @3 G5 y8 ~3 @
Dichotomous variable, 二分变量) V( d0 h8 [" S1 e
Differential equation, 微分方程/ ?& s" p% o- z+ W
Direct standardization, 直接标准化法3 F U5 K7 P1 p- C& x% ~
Discrete variable, 离散型变量1 b* w! F9 Y# r8 r8 [
DISCRIMINANT, 判断
1 N! p) n. S( kDiscriminant analysis, 判别分析: [2 k' g' b- `7 L0 {
Discriminant coefficient, 判别系数2 K( Q% X5 R& v' Y
Discriminant function, 判别值
7 w% l7 ^- e% {2 U6 BDispersion, 散布/分散度
! s: [! L2 w4 a" Y5 \Disproportional, 不成比例的$ _' g) [/ Y' |) K
Disproportionate sub-class numbers, 不成比例次级组含量
4 R4 T) o* D, T! l7 C! rDistribution free, 分布无关性/免分布
2 R8 W! r' c" RDistribution shape, 分布形状6 E' `+ k+ M% Z; D7 n3 K! p8 U
Distribution-free method, 任意分布法
7 i+ u, V. d% k, ]2 W1 Z+ xDistributive laws, 分配律
. X1 j8 S6 i; x- Q' xDisturbance, 随机扰动项 G" E I9 p: E& r* N) q* Q
Dose response curve, 剂量反应曲线3 N$ Y& \' ?. X3 j( Q
Double blind method, 双盲法
* ~! m* E, I/ ]/ zDouble blind trial, 双盲试验
- e( W ~* f( lDouble exponential distribution, 双指数分布5 K* o+ y, d/ Z+ n' b: d
Double logarithmic, 双对数- f+ \, q8 p7 A E5 V% Z$ d
Downward rank, 降秩
. Z' Y5 `% \6 y A( K' tDual-space plot, 对偶空间图
: s4 j; y8 H4 m, f* KDUD, 无导数方法5 \. V; I2 q0 k) a8 r
Duncan's new multiple range method, 新复极差法/Duncan新法) c5 J3 T7 m# O1 B3 L; X5 P; |
Effect, 实验效应
0 N( L! ~) M8 W- o. IEigenvalue, 特征值
$ _2 @4 X$ ]& kEigenvector, 特征向量7 E% y; T+ N( A4 u, R; T* Q
Ellipse, 椭圆* P) ~; {1 V, L* f7 v
Empirical distribution, 经验分布
9 C. H! u" y( l$ I' LEmpirical probability, 经验概率单位
1 \1 M! g" N3 `9 o$ XEnumeration data, 计数资料3 `* O" ?" N2 X/ J: J' c
Equal sun-class number, 相等次级组含量0 S; v0 w6 G4 {- e q4 p& r0 Z
Equally likely, 等可能
% M0 ^3 F' Y7 `( X4 ]! a1 t+ EEquivariance, 同变性
# _9 E& l& d. f. K3 z. Q, Z, B) s) rError, 误差/错误# h3 `* s' @$ O3 ]: X
Error of estimate, 估计误差
0 F& L: Z, G( F" \' K* YError type I, 第一类错误
2 I' {8 y+ `/ Y+ U7 HError type II, 第二类错误
) L/ j7 d5 E; J7 h9 m* T, OEstimand, 被估量# ]* R) @# W4 S* U5 U
Estimated error mean squares, 估计误差均方( y$ Z7 ~6 v, K1 C! h' I5 n! x3 Z
Estimated error sum of squares, 估计误差平方和, w+ W" t: Z! V, q( Q# m* N
Euclidean distance, 欧式距离
( @' k% J b3 ]9 xEvent, 事件
! j! `4 D: n7 o5 F( `Event, 事件
8 M; n( u1 c7 X# MExceptional data point, 异常数据点
7 S/ S, L" J! R: P; Z# }' [Expectation plane, 期望平面
4 ?7 j6 J1 j6 y6 {0 PExpectation surface, 期望曲面- O- X- K: [6 x- d; O$ R
Expected values, 期望值
: w1 a/ Q4 \4 \# r3 CExperiment, 实验
8 g' H( k8 v: r( o& Q. vExperimental sampling, 试验抽样
) M9 G1 X& f7 ]8 K+ ?Experimental unit, 试验单位
) }6 u- \1 l j o A- R* JExplanatory variable, 说明变量
8 M) r( G1 `) cExploratory data analysis, 探索性数据分析
1 v' b0 i5 m3 F# ]% @, L C" QExplore Summarize, 探索-摘要
0 {- ]3 Z* _/ ]Exponential curve, 指数曲线. A% L/ Q- C* w! I: g* ~8 Z/ ?
Exponential growth, 指数式增长# Q* C9 e9 k1 n) u, E
EXSMOOTH, 指数平滑方法 ; L( G( U% T# K* b) d
Extended fit, 扩充拟合) f9 M4 M8 f4 \8 ?
Extra parameter, 附加参数# ^9 N- g8 d3 Y' Q4 H$ g6 x2 V$ v
Extrapolation, 外推法* x3 T; ~# _/ S- f; _
Extreme observation, 末端观测值
" D% I: K) J; I" h* `Extremes, 极端值/极值5 H% G0 k/ n5 V( L' b
F distribution, F分布3 [6 k8 ]6 ^: n( n
F test, F检验
, D5 a% d6 a; u6 M3 OFactor, 因素/因子+ Z( r9 Z3 O$ G" r% K' V
Factor analysis, 因子分析
6 }7 l. D. Z( \3 U, t( O5 U) f& XFactor Analysis, 因子分析. `, y! }, n5 ^
Factor score, 因子得分
4 U2 E) x `) Y- P+ @" P' iFactorial, 阶乘6 e% `+ D- \) T7 U
Factorial design, 析因试验设计
% f% E, O& K2 W$ ]8 bFalse negative, 假阴性
; s5 v* _0 q: [+ nFalse negative error, 假阴性错误
" S* k( i, T3 kFamily of distributions, 分布族+ n# t4 b& G2 G1 X8 s
Family of estimators, 估计量族
+ u; [' x4 q, t4 CFanning, 扇面
% k I; J+ ^. {( s, |Fatality rate, 病死率
9 c) w* }. n6 v' N: h$ y8 eField investigation, 现场调查0 V$ O* b' R* i" O% I' c
Field survey, 现场调查
: F2 r# i9 b* v; U$ {1 U; rFinite population, 有限总体9 S0 R% v: G5 N, ]9 a
Finite-sample, 有限样本% l4 {5 C' B& p
First derivative, 一阶导数5 O7 {+ Q+ Q0 h+ R8 L2 n
First principal component, 第一主成分) f/ }" q& k# ~+ V" {
First quartile, 第一四分位数; e5 ^2 q& b4 ]/ t T
Fisher information, 费雪信息量
P9 {" S+ I& r) B! R) r u9 zFitted value, 拟合值$ N* ?- M) h' ~+ v
Fitting a curve, 曲线拟合
/ d' p% X }. E8 PFixed base, 定基' ^) }0 O. H( F D5 z
Fluctuation, 随机起伏
& J5 L" ]$ x7 \5 rForecast, 预测
( {9 l7 F5 j; R; p+ H& FFour fold table, 四格表
! }" p& l. ~1 x- r. j: {$ ] xFourth, 四分点+ v" h7 `( U0 \" S6 Q* H/ ~$ S/ f
Fraction blow, 左侧比率
$ K8 |% I: @; f+ QFractional error, 相对误差, C" F H5 B- V E& v( I
Frequency, 频率/ f5 N! R ]" V
Frequency polygon, 频数多边图/ U- y) A# s! u- D9 z% h1 t9 h
Frontier point, 界限点" l# }% F/ K6 }( \( h) z5 P
Function relationship, 泛函关系
: k8 v3 w2 }- }; O$ UGamma distribution, 伽玛分布( Z) F6 P: @# e* \1 x2 @' Y
Gauss increment, 高斯增量
) f2 o! @8 W) ]+ H5 S `Gaussian distribution, 高斯分布/正态分布% E' V( O q \! T9 `4 N& d! b- q
Gauss-Newton increment, 高斯-牛顿增量
# v. i, W0 g- f& L* e( [; Q3 {. n$ AGeneral census, 全面普查
, B( Y1 x8 ^5 G4 T$ h/ T+ a. k% FGENLOG (Generalized liner models), 广义线性模型
, h8 v* `: Z7 j" s7 D& |( M. h" }% o% aGeometric mean, 几何平均数2 f# o& o( Z. P* S- J' A: o
Gini's mean difference, 基尼均差* l& ^8 o1 p" C( b
GLM (General liner models), 一般线性模型
$ }" }+ B+ A0 A8 q; n- Q% cGoodness of fit, 拟和优度/配合度
) k7 b8 Y' T `6 H4 G5 d6 g& l* KGradient of determinant, 行列式的梯度
# R) G, C ?& W8 h7 [Graeco-Latin square, 希腊拉丁方; k G& S5 ]4 e1 c
Grand mean, 总均值* u8 w1 B, T/ S+ G
Gross errors, 重大错误
. I3 x" Y8 I( x3 y0 _+ _0 UGross-error sensitivity, 大错敏感度
/ o8 d7 N( b/ C& ^' n QGroup averages, 分组平均
4 Y- v6 _ [, X7 Y; [3 q, N, |Grouped data, 分组资料' X9 G2 {' o0 ~1 L5 K7 G% _
Guessed mean, 假定平均数
) c) G3 D+ j: b1 U7 V; z1 DHalf-life, 半衰期' y7 Z+ L" e+ x% J$ U4 Z% I
Hampel M-estimators, 汉佩尔M估计量/ b) d" t9 k/ X7 h; a. q
Happenstance, 偶然事件 W% M4 y/ |1 {( K; {3 w7 \8 p
Harmonic mean, 调和均数8 }) c) U2 ^* F% I' C. H' n# L4 G
Hazard function, 风险均数
8 }7 q7 Q. ?1 l* p/ X$ t/ I$ ZHazard rate, 风险率
( A, Y. Z7 Y' S& \Heading, 标目
2 E/ u/ V r# x; J6 EHeavy-tailed distribution, 重尾分布
. L2 A- C% d% K9 {& mHessian array, 海森立体阵
1 B: H" e! U* I% N2 ZHeterogeneity, 不同质
$ A0 U9 _, D3 r$ LHeterogeneity of variance, 方差不齐
$ W$ u# r: ?- w( @- vHierarchical classification, 组内分组. e& j2 a+ e- q! \+ [& v
Hierarchical clustering method, 系统聚类法$ ^8 l, s* w; P M
High-leverage point, 高杠杆率点3 g! Z, Q- g3 F5 z: o% x" ^! S
HILOGLINEAR, 多维列联表的层次对数线性模型
. z5 I/ G" u, z _7 u, n9 ]Hinge, 折叶点% w1 B ^ `: H% W( X; y: C
Histogram, 直方图$ \4 F9 O2 @7 |
Historical cohort study, 历史性队列研究 8 v( r/ d( w# c# t6 v O+ c3 o, K
Holes, 空洞8 U6 o" g# G8 r; u) l
HOMALS, 多重响应分析
2 T( }. a$ P: {( u" Y6 KHomogeneity of variance, 方差齐性5 W# }- {3 V; `
Homogeneity test, 齐性检验
5 R" d9 ~/ F2 kHuber M-estimators, 休伯M估计量/ p* E# [. S% V, f1 H+ X$ x$ L1 o
Hyperbola, 双曲线
( f( y; x K, L7 N2 gHypothesis testing, 假设检验
$ J5 ?, \1 x( v8 z5 kHypothetical universe, 假设总体
; S6 v4 r/ m7 a e9 KImpossible event, 不可能事件
4 I& r7 @. Y$ F* e6 T) ~ jIndependence, 独立性
' s' b) e7 B" X% i) p% I( DIndependent variable, 自变量
4 a1 s \8 ~$ R- M& X: CIndex, 指标/指数8 b; M8 N) d) W( ^* f. [
Indirect standardization, 间接标准化法
' }5 P% _/ x7 s7 jIndividual, 个体# n! o. [% E, e) V$ }, q$ `; ^
Inference band, 推断带
: D: {, Q" G' X8 r# ]7 l2 NInfinite population, 无限总体) Q- S9 ]+ X( S9 g
Infinitely great, 无穷大( Y( f T, r, a6 R& ^" f
Infinitely small, 无穷小
* _4 T4 y2 w% L; g0 KInfluence curve, 影响曲线
& }' d* V5 B5 p4 V _ XInformation capacity, 信息容量; `* m- h3 i; o/ I
Initial condition, 初始条件3 j1 V& t' W) S1 B" ]
Initial estimate, 初始估计值
9 ]6 H7 m# q- y5 r0 zInitial level, 最初水平/ E# ^! Q/ O) c1 Y; A0 k& t! h6 v+ Q
Interaction, 交互作用, \7 p& U$ A) @
Interaction terms, 交互作用项
" ]! M5 D" t1 F$ Q% jIntercept, 截距
7 l4 A7 G9 U5 r5 jInterpolation, 内插法8 a4 I+ D( g* P2 p) D
Interquartile range, 四分位距) M# ?4 S2 n, z. Y8 _
Interval estimation, 区间估计
" F5 i" p- J9 h7 B0 c2 u$ pIntervals of equal probability, 等概率区间1 W6 M4 E% L2 ~$ g2 `
Intrinsic curvature, 固有曲率7 L W/ @% I5 e& L- t) p! f: d
Invariance, 不变性' i6 M- b7 A* M6 ~9 d
Inverse matrix, 逆矩阵
8 m8 c( Y+ M" }' Y \4 iInverse probability, 逆概率
+ X& a3 i. T C- c" I% [& o7 ~1 B# t7 T3 uInverse sine transformation, 反正弦变换
, ~6 Z" N4 Y( _* }Iteration, 迭代 ' e% v+ H( y! L T" w/ ^0 ?
Jacobian determinant, 雅可比行列式
4 E1 Y: Y& d( Z8 a; F. [" C6 Q( AJoint distribution function, 分布函数
$ p8 X" L$ v& a# C+ gJoint probability, 联合概率
6 J: H& q3 n: a1 e( M& SJoint probability distribution, 联合概率分布- \: e* m2 |3 `
K means method, 逐步聚类法
& u5 U9 U, N0 W7 L% O" e0 t; x6 y; pKaplan-Meier, 评估事件的时间长度
! T+ b; `! N/ u, yKaplan-Merier chart, Kaplan-Merier图7 C# N9 \, O$ ^7 E& c" y" [8 \
Kendall's rank correlation, Kendall等级相关
$ q+ ]1 l. D1 SKinetic, 动力学
" o. e* b2 l mKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验, N: u2 i: S+ Q% m2 T. Y
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验* `+ k0 H) x& M$ r/ D$ ]/ S& ~- N
Kurtosis, 峰度, }* T& A( Q l* \7 t+ p
Lack of fit, 失拟
) u0 u) p8 F( ^6 H1 E' T2 N/ \3 NLadder of powers, 幂阶梯" O( L d$ |& L; U. x1 w u
Lag, 滞后/ [$ I8 b- q4 J
Large sample, 大样本
2 p& j1 z0 ?4 |+ N7 j+ S: ?Large sample test, 大样本检验
- g6 j% D/ k0 N& z! {Latin square, 拉丁方! c- q4 } t4 B6 }& c. X
Latin square design, 拉丁方设计
4 `) c T$ G f9 w! P& n5 _Leakage, 泄漏
7 a: h6 ^) `& ?& ?- }: N4 z% }Least favorable configuration, 最不利构形# j) T3 L/ M& o) Z$ G
Least favorable distribution, 最不利分布
; ]! {' C+ c8 A9 f: E+ WLeast significant difference, 最小显著差法6 t4 c3 c4 N% ~3 O1 ~2 L2 w' p! } l: e
Least square method, 最小二乘法 Z+ h& _- ^. n$ n0 A
Least-absolute-residuals estimates, 最小绝对残差估计9 x6 [' c3 u4 a1 L3 J7 ^
Least-absolute-residuals fit, 最小绝对残差拟合
2 }. `8 O7 M$ g# {& |Least-absolute-residuals line, 最小绝对残差线
4 T: G4 H8 ?7 U4 \Legend, 图例* F5 Q; x2 k' n& l$ V
L-estimator, L估计量
k8 }1 J) J# LL-estimator of location, 位置L估计量
4 j7 N. M2 Q/ F, VL-estimator of scale, 尺度L估计量7 m% I( E7 i1 Y! l2 F& N2 N' i
Level, 水平
k0 W* {+ {% bLife expectance, 预期期望寿命& d- Y: C7 M. w7 F
Life table, 寿命表2 ]' {; T" D/ ?
Life table method, 生命表法& {; ]- k: q$ H5 f4 L6 q. [/ t
Light-tailed distribution, 轻尾分布
- u7 i' h; y/ X" VLikelihood function, 似然函数0 B/ o2 @ X. J( R4 N1 D" {
Likelihood ratio, 似然比
& P3 ~* k5 ~6 x0 ]. w$ {2 ]8 Yline graph, 线图! F: t( V# V4 h' `$ f4 j
Linear correlation, 直线相关
; j p0 A: ^4 D8 DLinear equation, 线性方程! l6 F- i4 t) [# M( ^5 s) T
Linear programming, 线性规划0 G# E! Y5 f _& x$ T; G
Linear regression, 直线回归1 B" d' {5 x9 b/ v |1 I
Linear Regression, 线性回归( W9 w) H q& p- a% r+ L& n, h
Linear trend, 线性趋势
% L3 m5 C! E; O8 d4 ~/ h$ W1 ZLoading, 载荷 . ?7 J0 K( w7 i5 |" M
Location and scale equivariance, 位置尺度同变性
/ V$ R6 G6 @% [. ZLocation equivariance, 位置同变性
; L* A$ j5 \2 m/ A7 ULocation invariance, 位置不变性
1 C; f& ]0 x0 P) U- ]7 H- A) SLocation scale family, 位置尺度族; o$ T# n8 ? n h# E
Log rank test, 时序检验 3 [( V4 n/ ]- \6 ~' O* D% m [% O& a6 \
Logarithmic curve, 对数曲线
6 n* F3 @" i+ ?) z( gLogarithmic normal distribution, 对数正态分布" \; O8 K1 c8 Y+ _, C
Logarithmic scale, 对数尺度- s$ ^/ D& O3 ], _
Logarithmic transformation, 对数变换
" x- X$ \$ C G2 b( j2 RLogic check, 逻辑检查
5 F+ L4 i8 a% JLogistic distribution, 逻辑斯特分布" M) D. Z* u# Q$ f* B
Logit transformation, Logit转换" _( |, {- o8 q) O+ y) s: w) a- |! m
LOGLINEAR, 多维列联表通用模型 $ u6 |: x: w: q) \* H1 y
Lognormal distribution, 对数正态分布
3 ~4 T7 O( k4 k' BLost function, 损失函数
* W9 @% L% d; U8 K8 vLow correlation, 低度相关' a. }* N* c1 M
Lower limit, 下限: N: C8 u! `- \; d5 a4 z$ L% h2 {
Lowest-attained variance, 最小可达方差4 I7 g1 i! a6 i( c) @
LSD, 最小显著差法的简称- N N7 q( k$ i' z' @$ {; W
Lurking variable, 潜在变量& f% X( b' e! _, L" z# I% M
Main effect, 主效应
/ J. T" }. p( l# V2 h0 |8 O+ V/ F2 MMajor heading, 主辞标目
0 a: }" V3 ~8 t: w5 o0 nMarginal density function, 边缘密度函数) H, [" H( R+ T6 a
Marginal probability, 边缘概率+ n5 l* p! W7 ] \. k8 T
Marginal probability distribution, 边缘概率分布
$ }6 X7 H' N3 p7 H2 MMatched data, 配对资料
8 @ b) k6 M7 } W( fMatched distribution, 匹配过分布9 k" S. f" n+ o0 ?
Matching of distribution, 分布的匹配) T+ {) c, L8 L- m
Matching of transformation, 变换的匹配, U* A4 |# H3 N" Y- I9 M3 q
Mathematical expectation, 数学期望, ^2 |# {+ k! i, E
Mathematical model, 数学模型1 l! o5 S O/ c/ i
Maximum L-estimator, 极大极小L 估计量
$ T- \ l* C! G+ DMaximum likelihood method, 最大似然法% t4 ]8 B' R0 d( U* J9 ~
Mean, 均数6 E9 k {. `0 j% M8 R J0 q
Mean squares between groups, 组间均方
$ \1 }6 Y R$ mMean squares within group, 组内均方9 a$ K3 V, b0 ]" _4 b) b
Means (Compare means), 均值-均值比较7 o& |/ T1 a e9 S
Median, 中位数
+ t. X& @3 E; T5 Z5 Y- ZMedian effective dose, 半数效量) F6 T- @% T! R; E$ y
Median lethal dose, 半数致死量
; y- Q. Y0 j" Z, A5 I8 `* bMedian polish, 中位数平滑8 {+ P! U# x; l5 j
Median test, 中位数检验
' [1 u/ c! I; U3 |7 |9 L x" OMinimal sufficient statistic, 最小充分统计量2 A0 ^, A: e; B, `, b* o6 k( ?
Minimum distance estimation, 最小距离估计; x' [2 z$ P+ ^/ }5 I* o5 l
Minimum effective dose, 最小有效量( _' t, A) e; f, l- M
Minimum lethal dose, 最小致死量
- L( \0 H& S- d8 a" r. TMinimum variance estimator, 最小方差估计量: _: i- |; ~% P
MINITAB, 统计软件包
0 E3 q( j) n' P! B9 S$ ?) oMinor heading, 宾词标目8 H" |$ p+ ]. ]
Missing data, 缺失值
/ ?( m% [2 o T% l# eModel specification, 模型的确定. p; c" p3 M$ Z- E5 M. y
Modeling Statistics , 模型统计
6 i' h; C( j1 _+ L% @Models for outliers, 离群值模型( l3 j- c1 s4 P6 r- D) d
Modifying the model, 模型的修正
* Y& s/ m- A$ U. r$ o% c+ }Modulus of continuity, 连续性模- K2 d' e, s1 i; r9 X# |
Morbidity, 发病率
0 K, R/ Q3 w8 t5 I& EMost favorable configuration, 最有利构形
; n5 z7 R2 g3 {: H. WMultidimensional Scaling (ASCAL), 多维尺度/多维标度7 P1 e. {( M( p9 g+ R0 \% A
Multinomial Logistic Regression , 多项逻辑斯蒂回归) ?/ u3 G9 V3 M2 l8 `' Z
Multiple comparison, 多重比较
. q1 C$ Y& W' E& c9 _Multiple correlation , 复相关
5 {# @, q4 S4 \& z& GMultiple covariance, 多元协方差" U9 W4 D. ^/ u8 C
Multiple linear regression, 多元线性回归
: D% ]" d" I/ [0 J2 `6 bMultiple response , 多重选项
$ |8 p7 D+ L% E3 P) UMultiple solutions, 多解+ ~5 h+ s" M7 d: D% X6 u; P
Multiplication theorem, 乘法定理
( I N9 K8 s* \. c0 H( l7 JMultiresponse, 多元响应4 l3 _: s/ n2 ?* ]3 J3 n! X) l( P/ u
Multi-stage sampling, 多阶段抽样
! D6 d; {3 C3 p; Q. p' AMultivariate T distribution, 多元T分布: E' W- i" {. z
Mutual exclusive, 互不相容! O& X, S" ^" s* M9 H5 @2 A4 o
Mutual independence, 互相独立- \1 b# m# i1 K* a' p
Natural boundary, 自然边界
5 R; f4 q# @4 u& v9 ]- c/ m! vNatural dead, 自然死亡
1 X/ V! G: h: N9 s% {Natural zero, 自然零
* ?; M: U3 G+ M2 d) lNegative correlation, 负相关
$ r: g5 r9 Z0 X# @7 f6 cNegative linear correlation, 负线性相关, m3 _4 G/ i7 N0 V( f) B' Z
Negatively skewed, 负偏
9 h% {* ^& R$ f, `( P& v! H1 `Newman-Keuls method, q检验& M" d9 U! z' z6 c. N9 q2 R) A+ E
NK method, q检验
. W x. g1 u; `2 JNo statistical significance, 无统计意义
& S M$ S' ~ P7 D) m' ^Nominal variable, 名义变量
. ^/ x) {3 o% qNonconstancy of variability, 变异的非定常性
9 s( E8 T" W3 X3 t7 pNonlinear regression, 非线性相关$ }- F1 \% i; _# y/ z9 m! b; D
Nonparametric statistics, 非参数统计
: U- H5 |3 W! {# s' p# p% BNonparametric test, 非参数检验0 I( @( e( N, k* A' x1 k9 N- z
Nonparametric tests, 非参数检验
9 Z* Q& l/ m" N: N" b6 | y% _# QNormal deviate, 正态离差5 q% _- Y8 j3 M5 c( V T
Normal distribution, 正态分布1 P2 ~: H$ Z! A0 f- K: l
Normal equation, 正规方程组1 j! C& q8 c j, Z: w8 Y
Normal ranges, 正常范围# o5 a* E: V- l q. i) ]& M
Normal value, 正常值
0 l& h) K5 c% o" A: r5 }5 RNuisance parameter, 多余参数/讨厌参数5 D$ b! N) \% s* q0 R. R1 s- e
Null hypothesis, 无效假设
- o% z1 L* D; q1 INumerical variable, 数值变量
Y$ }8 T: O& A9 g! T* x, GObjective function, 目标函数
8 Y# i& n( S$ F& L' [Observation unit, 观察单位0 U6 O; S$ z# v8 j0 R6 A
Observed value, 观察值1 {. E( v! S3 ~: D. v$ B) m
One sided test, 单侧检验5 ^ a4 {1 H/ {2 w! }' Z
One-way analysis of variance, 单因素方差分析6 w6 Z% U' `) e/ ]* t4 z4 u& W, _% E
Oneway ANOVA , 单因素方差分析
9 j, r1 A. B5 e# o5 l* yOpen sequential trial, 开放型序贯设计6 l7 f/ |) S% g" L K7 Q; V5 M* u
Optrim, 优切尾
7 W0 V4 c8 {, s# Y4 e* q' z4 nOptrim efficiency, 优切尾效率
& O/ y, G( T Y2 BOrder statistics, 顺序统计量
" p \" N) S& l$ }/ hOrdered categories, 有序分类
4 k; b7 h+ d# _1 y: Y5 g5 fOrdinal logistic regression , 序数逻辑斯蒂回归: Y. r' y7 z Y& L5 s o# Q% U( G
Ordinal variable, 有序变量* {9 j! ]1 m* t3 ?8 }4 L C& ~7 ?; i
Orthogonal basis, 正交基, j' t- l1 @8 ^8 N; v6 Y
Orthogonal design, 正交试验设计+ l. e9 `; n- K3 x
Orthogonality conditions, 正交条件# Q9 @( |6 P1 O# T9 j
ORTHOPLAN, 正交设计
7 ] H* L6 [ r* `- E7 b" v+ w& YOutlier cutoffs, 离群值截断点* v8 m8 F* P+ v% O
Outliers, 极端值; x2 Y' l! [4 l- k/ Z1 V
OVERALS , 多组变量的非线性正规相关 " ]7 n1 J: o: E+ p1 G; v1 i5 |. o% h, N
Overshoot, 迭代过度/ C& F! i) Q( i
Paired design, 配对设计
) i: Z8 [: `* i0 z" \Paired sample, 配对样本
- C* R8 T8 q7 PPairwise slopes, 成对斜率. h$ K: b8 ?* T0 p0 y
Parabola, 抛物线
% Q; t/ G& ]4 ], Q( PParallel tests, 平行试验4 o, ?& l2 e+ G; `% y; ?
Parameter, 参数! Y2 T1 ^, y0 z" p% L
Parametric statistics, 参数统计( i+ `3 D, G: C H) D2 X
Parametric test, 参数检验5 s8 \9 ]# m3 }# w, V6 x
Partial correlation, 偏相关6 g& Z% C) g y
Partial regression, 偏回归
( i0 U' m+ }- lPartial sorting, 偏排序/ e/ ?' t: j. n7 }- j3 J5 p
Partials residuals, 偏残差" U7 _) Q- v( I& R# r, s
Pattern, 模式3 _' j6 }& `; u. p; m
Pearson curves, 皮尔逊曲线
- b9 W: e- b C9 @Peeling, 退层" h' A, n6 O6 ?6 L" I& n
Percent bar graph, 百分条形图
7 e x' N( c1 x$ z7 wPercentage, 百分比, `9 K, q0 ^, D& v! H1 \: t& y
Percentile, 百分位数
: j3 }+ {: M2 V, b( RPercentile curves, 百分位曲线1 B0 J: J5 N& N8 n2 j! W
Periodicity, 周期性
+ E! q% e9 b( \: nPermutation, 排列
( N0 ]* h# P+ Q8 {: C, dP-estimator, P估计量2 j4 Z- S3 U- T
Pie graph, 饼图4 z7 U, T' B" p, u, V! h1 [
Pitman estimator, 皮特曼估计量
6 q% s/ R, I, ^; x9 Z/ ~: cPivot, 枢轴量2 S0 m( f3 ^5 y* |; B
Planar, 平坦4 t" k. g2 d& w4 R& @
Planar assumption, 平面的假设% _% @2 x0 `7 c: o8 Q% a. y' G: k6 O
PLANCARDS, 生成试验的计划卡
$ {! Q8 w+ I$ I0 O' E0 mPoint estimation, 点估计( N. t9 P9 P( @4 m
Poisson distribution, 泊松分布
& ~0 Y6 a/ k) y. YPolishing, 平滑
. Q7 [2 p7 \; o% v% WPolled standard deviation, 合并标准差5 A9 p! ^0 e- v9 R8 [
Polled variance, 合并方差/ R$ L. @1 R( k3 Y* q }
Polygon, 多边图
' _9 D; \, |) U( w1 mPolynomial, 多项式! o8 J' E1 K- E, W9 |
Polynomial curve, 多项式曲线
; t' e3 M7 M/ N$ I! R; pPopulation, 总体
! v: }: s9 O9 |2 ]+ [+ ePopulation attributable risk, 人群归因危险度4 \; `% {: ~/ p) q
Positive correlation, 正相关' D8 u/ ^, v4 @9 f" N1 n$ Z
Positively skewed, 正偏
( r0 S1 n8 M2 V3 lPosterior distribution, 后验分布( u$ H' I, `$ J, c# E
Power of a test, 检验效能
1 _1 r2 `+ M( I, v; V8 aPrecision, 精密度
2 X1 P/ a' p7 I% P, _- l0 e5 xPredicted value, 预测值$ `2 U+ V$ n5 l- X& ?4 u
Preliminary analysis, 预备性分析9 h+ e0 S! Q& |
Principal component analysis, 主成分分析
7 a% H( g) x4 U4 ~0 ?# v( sPrior distribution, 先验分布5 `4 L$ v9 L: I8 p2 k
Prior probability, 先验概率
/ }. \0 S$ p- t1 }Probabilistic model, 概率模型+ [3 w% n4 {9 B |( B5 r
probability, 概率
6 k# U" i4 J0 g! rProbability density, 概率密度& v" _8 \% P8 T# L
Product moment, 乘积矩/协方差2 Z% h% _ v4 l$ [$ A
Profile trace, 截面迹图
: `- m' O% S8 r+ @ Y9 }5 H3 JProportion, 比/构成比; ]0 t6 ^" J7 M- @6 c
Proportion allocation in stratified random sampling, 按比例分层随机抽样+ N" ?/ q, b+ H6 M: Y" Z
Proportionate, 成比例
J. Y0 F% Z$ |3 TProportionate sub-class numbers, 成比例次级组含量5 ]. ^9 R9 h3 G
Prospective study, 前瞻性调查% P+ U+ J: V! C1 G: x' L6 }
Proximities, 亲近性 7 z% _3 a: q' |; A
Pseudo F test, 近似F检验
" |/ L" j, j; I8 qPseudo model, 近似模型
/ U# F6 D2 d7 u; RPseudosigma, 伪标准差
; A) f" u, z/ Y. a5 ]. g5 s' GPurposive sampling, 有目的抽样4 w# Y% B( ~$ h3 T$ ^! l0 X9 o6 ]
QR decomposition, QR分解0 b4 P- {( o9 f+ m( B" W. p1 l* |
Quadratic approximation, 二次近似
: i1 w. c9 G4 lQualitative classification, 属性分类( C1 X; }" D/ O8 h7 f# O
Qualitative method, 定性方法( B' j% W' U5 l9 P! l4 ?1 H
Quantile-quantile plot, 分位数-分位数图/Q-Q图
. i* y& _' p3 {; ^ ]* `/ \Quantitative analysis, 定量分析, v3 b6 R! S9 h, o: u# |
Quartile, 四分位数
/ @& d0 d( e5 C9 x) }Quick Cluster, 快速聚类
) f8 ~+ M5 G+ r1 K/ q6 ARadix sort, 基数排序
0 Y9 |$ d9 \# h5 \5 p2 tRandom allocation, 随机化分组; V' c Q3 C U$ @+ q
Random blocks design, 随机区组设计
; s. @4 x7 H, iRandom event, 随机事件$ v; ]/ K* d/ ^/ _
Randomization, 随机化' I. N3 w* m) S4 J
Range, 极差/全距& j% H5 N9 k1 d9 C+ ~
Rank correlation, 等级相关8 j, ^1 q$ v$ g3 m
Rank sum test, 秩和检验
o& ?% _* \. yRank test, 秩检验
& ]+ C5 t$ _) ~/ f5 P5 {6 sRanked data, 等级资料
( g4 z( c. k5 [2 Q5 D% m0 GRate, 比率3 ^) r8 k5 i9 ?% b' P
Ratio, 比例( }& ^2 \7 D/ G0 J8 }7 k$ U Z
Raw data, 原始资料* O" V# Y1 X, Z
Raw residual, 原始残差& i# Q' V5 a8 z4 E# d* s; R' e
Rayleigh's test, 雷氏检验
# t0 c. @& ^0 S2 E A8 T2 q3 N( [Rayleigh's Z, 雷氏Z值
* ^0 g# x6 S8 F! r( W# v% o$ qReciprocal, 倒数
; H8 e! s$ l g$ ^2 T8 {& wReciprocal transformation, 倒数变换
* q0 w: G5 w6 Q8 J. CRecording, 记录5 ]0 [' W' }, q
Redescending estimators, 回降估计量# \+ ~* r1 H6 A- o% B1 T {$ a$ V
Reducing dimensions, 降维9 ~2 F) a6 C. P% f4 i+ c
Re-expression, 重新表达2 f: N/ _: ~7 W+ S( k7 d# G# e
Reference set, 标准组& Z/ H( i7 E9 A: h
Region of acceptance, 接受域
1 c2 y! Q3 N& V3 ~6 e5 c& fRegression coefficient, 回归系数
% w; A% M( U+ y5 d/ E! y9 \5 b" ERegression sum of square, 回归平方和: |& i. b- y) L- c z
Rejection point, 拒绝点
% u) f8 q4 g* Z4 ] l) N* X6 \; b# ORelative dispersion, 相对离散度
$ R6 c& m3 I1 y2 VRelative number, 相对数
! m8 Z8 f: E% s" |$ [Reliability, 可靠性- @0 Q, B Q- S( {! B+ p: U& E+ N6 `
Reparametrization, 重新设置参数, L& K/ l8 E6 H! W; t
Replication, 重复8 C$ F9 O3 O2 h2 G D
Report Summaries, 报告摘要
! W& k. o+ J5 a, b4 B9 d6 s: AResidual sum of square, 剩余平方和
% ?- ]0 D2 Q. j9 B I' eResistance, 耐抗性" ?$ P* Y& h& e( ]7 F [
Resistant line, 耐抗线
p) G$ ^5 U' _0 O; P. `7 @. aResistant technique, 耐抗技术
( U' z5 H8 F: C: FR-estimator of location, 位置R估计量. m& C0 \: D% n; M
R-estimator of scale, 尺度R估计量) \. b/ f' ~" J8 Y3 L- e) K
Retrospective study, 回顾性调查& E- \3 o3 C9 j( A
Ridge trace, 岭迹
}" N8 T! }4 }( c# _% VRidit analysis, Ridit分析7 F) @: y/ V" F# Z- G0 M
Rotation, 旋转
! N, a! z G( v$ {. iRounding, 舍入: b. h9 b7 x6 A& t4 z2 D; P# p [3 C
Row, 行4 ~. j$ ~: z# B, ~! h p
Row effects, 行效应
0 Z& ~& Y6 H( O' B. v' q+ r+ WRow factor, 行因素3 J# \7 H8 C# ~# U& Q! k
RXC table, RXC表. c+ S @" s8 m, |
Sample, 样本9 Y& m y. f8 |# D+ e! l
Sample regression coefficient, 样本回归系数
0 V V% @8 Y" J9 m) d* Q. ~Sample size, 样本量- b: d$ K f Z( d" \
Sample standard deviation, 样本标准差
! c& E! f4 [) R" }6 r0 ~+ m, hSampling error, 抽样误差. h; x: z3 j6 w8 M( g5 j E- {
SAS(Statistical analysis system ), SAS统计软件包
( o+ |$ Q4 l+ @0 @! U PScale, 尺度/量表) h" ]" e! Z9 v. B0 v
Scatter diagram, 散点图
" I% K- X) M# g$ S; c) ESchematic plot, 示意图/简图
* l$ f2 q0 \- A7 h3 h9 AScore test, 计分检验
/ ]- f- z; q* yScreening, 筛检
7 `% I; \6 J" U5 MSEASON, 季节分析 $ Z( P7 q" K# C1 t/ `
Second derivative, 二阶导数$ @( j9 E8 ~3 `0 }/ @& r: ^/ ?
Second principal component, 第二主成分
4 }! v2 p9 Z9 I, ^! h0 TSEM (Structural equation modeling), 结构化方程模型 $ v* t& V# A2 g& G, M: X
Semi-logarithmic graph, 半对数图
3 ?8 B2 p5 F* N: W: D9 Z/ ASemi-logarithmic paper, 半对数格纸
5 L, ^, ]6 j# h! y! xSensitivity curve, 敏感度曲线
8 E7 m& V& k: z: j" O" E/ {: pSequential analysis, 贯序分析- i9 ~1 Y* j! X; Z" x; w( @8 g
Sequential data set, 顺序数据集+ t! o" J4 d+ z# X6 n' N& w' B5 I1 |# o
Sequential design, 贯序设计
. t3 }, H7 A1 V1 w8 r; ASequential method, 贯序法
7 h2 ]5 ?4 E8 E0 b( Q+ NSequential test, 贯序检验法: c7 \3 Z: f! b" z* e: h0 y8 J1 C& ^
Serial tests, 系列试验
- U6 `8 v5 N4 f! T9 {5 y U1 EShort-cut method, 简捷法 $ V2 h$ B) _) B) D$ `0 Q
Sigmoid curve, S形曲线
' o! a0 }( S e' a$ A+ A( V' xSign function, 正负号函数
+ ^9 o) o6 f: B. l1 d# ASign test, 符号检验5 C1 ?; Z4 Y+ j, A' I
Signed rank, 符号秩
* e+ O% l; S7 T# o$ \/ M" X: B; rSignificance test, 显著性检验% | K0 E7 _( _" i
Significant figure, 有效数字
. C2 f8 F3 {1 F; G( H+ V1 Z8 USimple cluster sampling, 简单整群抽样
, T8 G4 ^5 O5 D% |+ @+ cSimple correlation, 简单相关
0 x1 ] I# T+ i# Q+ _% GSimple random sampling, 简单随机抽样/ E8 v. F, O8 R
Simple regression, 简单回归
! Z, B3 t& F8 \/ X3 T, J2 tsimple table, 简单表
5 `/ ^/ ?- ^% W# lSine estimator, 正弦估计量4 B, T6 Z4 _" z; ^1 {
Single-valued estimate, 单值估计
+ o8 o. k' ~3 xSingular matrix, 奇异矩阵
: z g8 c5 K) J/ u3 ~Skewed distribution, 偏斜分布
1 V$ K# b" ~" A3 l" u! FSkewness, 偏度
" Q/ e( J" P9 P8 ~, iSlash distribution, 斜线分布
' v H8 `3 i5 d; b* t; C QSlope, 斜率1 m2 l6 f% W: T- \% D/ w
Smirnov test, 斯米尔诺夫检验
& j% a' L0 O0 \. \# VSource of variation, 变异来源
; `/ W+ P3 [: I8 L9 T; P9 B cSpearman rank correlation, 斯皮尔曼等级相关
& s% w! C. u& t5 T) i8 q1 aSpecific factor, 特殊因子
6 }# L+ e/ ^2 q4 JSpecific factor variance, 特殊因子方差
1 W. ] O( u( c$ L8 P- BSpectra , 频谱* M I9 W/ s% Q# @2 v
Spherical distribution, 球型正态分布( A7 F; ~5 o3 E6 O$ m: y/ d: B) w
Spread, 展布
8 H& l( o% H. U+ C: DSPSS(Statistical package for the social science), SPSS统计软件包7 [) g4 |+ e. F- {) `, v. O
Spurious correlation, 假性相关8 b+ _/ I C% T1 L# C- F
Square root transformation, 平方根变换# }. S5 ^1 a. z% T5 j& R/ i2 _/ z
Stabilizing variance, 稳定方差
. i/ }5 Q# B i& p9 M: iStandard deviation, 标准差
) O/ y/ @! Z. g; \! @2 A- q/ Z$ p* JStandard error, 标准误8 \* N- q* A8 D/ k; ?7 }
Standard error of difference, 差别的标准误. b% m3 D/ B" y% p: `
Standard error of estimate, 标准估计误差3 @# k: p. {# g- B
Standard error of rate, 率的标准误7 V# c8 r5 {) u6 ]9 g
Standard normal distribution, 标准正态分布* w% N1 E3 }: y" @4 }
Standardization, 标准化& e9 Z6 p+ E+ C6 q$ {* r. w
Starting value, 起始值) r3 }7 G- T; m2 k6 J
Statistic, 统计量
, a' c9 F; @6 I0 D0 H- [Statistical control, 统计控制
( P7 ?# `% a" ?/ qStatistical graph, 统计图0 S4 K+ ?# ~, G: V$ K; n9 a7 b
Statistical inference, 统计推断
/ t0 o5 [2 t* j: z) q: J3 UStatistical table, 统计表 c2 x5 j7 v" u; c$ j9 J
Steepest descent, 最速下降法
+ Y5 m6 C* C9 Q& W4 EStem and leaf display, 茎叶图
, O( T; b2 T) W4 R; uStep factor, 步长因子
! M! K; c) u& I$ j2 M; ZStepwise regression, 逐步回归 [6 w! r* P& F. w5 u
Storage, 存
. a. k: W4 G' ^Strata, 层（复数）) p1 m# S! E q: a! e
Stratified sampling, 分层抽样8 v e7 G0 o8 S& j
Stratified sampling, 分层抽样* B9 O8 i5 e! ] r2 M
Strength, 强度! H+ Y- [/ ?/ I
Stringency, 严密性, w# Q; Y1 Z `4 T. k* I
Structural relationship, 结构关系
) F+ U5 y/ v( u5 w# Y* eStudentized residual, 学生化残差/t化残差
/ _; q* o7 \5 D0 c; m q* n! ESub-class numbers, 次级组含量
( V9 q7 ^, M' |6 x( O! ZSubdividing, 分割, [; P9 P; M+ W, j, e
Sufficient statistic, 充分统计量
9 q% q& {# C, eSum of products, 积和
% G9 a2 B! w+ \# o5 RSum of squares, 离差平方和
7 R" V5 D3 v! {1 a) W, [Sum of squares about regression, 回归平方和( N- |% M0 `7 }1 m" L" s
Sum of squares between groups, 组间平方和
6 g, M* a$ E2 b) G! |7 wSum of squares of partial regression, 偏回归平方和
* U) R5 N1 U/ Z, u1 {Sure event, 必然事件
3 a0 C9 L6 @' P4 ESurvey, 调查8 `8 N9 Q* {0 o) v3 D
Survival, 生存分析
6 f, y/ H/ Y& m- B" F% V9 CSurvival rate, 生存率
+ G7 h/ n) F. o+ }, pSuspended root gram, 悬吊根图0 r: z$ C: m2 [2 _9 k
Symmetry, 对称
! ] }7 E+ l3 v8 hSystematic error, 系统误差
' s" ^( Q+ F3 dSystematic sampling, 系统抽样6 d; d5 U, u4 p6 A
Tags, 标签# a- _% n B ~( V6 ]( u& l
Tail area, 尾部面积. X6 W* R4 X$ o" b$ l0 T N
Tail length, 尾长7 `9 o/ V( u6 w2 ]
Tail weight, 尾重
; J! d4 @. u, ^, eTangent line, 切线3 `* K6 e3 ? M( u: T- h
Target distribution, 目标分布0 K, S/ k& p5 `: X8 X/ I4 l
Taylor series, 泰勒级数
( s, @9 ?3 z O+ a3 n& V* v+ dTendency of dispersion, 离散趋势' Z/ e- h) Q0 t5 E3 l! I! {7 M
Testing of hypotheses, 假设检验& h& L6 Q' `! B* K& b
Theoretical frequency, 理论频数# N$ ^. l- @% I0 t" Q
Time series, 时间序列, ^+ s. @% |- g5 {0 J) ? o7 g& k* h
Tolerance interval, 容忍区间
( C( v& G) C, x: OTolerance lower limit, 容忍下限
& I+ I. M% l6 oTolerance upper limit, 容忍上限
0 }( @7 q" K. D1 `$ o7 s: v* }Torsion, 扰率
# r. j! F# L6 v# I9 \. sTotal sum of square, 总平方和9 a% A% P* I, P
Total variation, 总变异 W/ }; E ^% h3 M) [- j. P: d- v
Transformation, 转换
7 `' U; @4 S5 [4 d! YTreatment, 处理! f2 w" U: l2 q: R
Trend, 趋势) f3 Q6 m ?$ a) S7 e y# a
Trend of percentage, 百分比趋势) G/ O# l( ?% O6 I# ?- e
Trial, 试验3 ~$ J4 Y& \8 v& W% z9 f( }4 |
Trial and error method, 试错法
, b* w7 \0 l2 P$ x( ^Tuning constant, 细调常数
0 @2 v4 `" ^3 ^! T2 _3 o( iTwo sided test, 双向检验
% [ _8 K$ f0 _" H/ i- MTwo-stage least squares, 二阶最小平方
: x+ ~8 z. @7 A6 f/ B3 e6 a d) CTwo-stage sampling, 二阶段抽样
3 x" u% W: L G, \2 U' z4 X: @8 X/ iTwo-tailed test, 双侧检验% _# R7 A8 y& w) T8 ^6 {' q* a+ H2 x# ?
Two-way analysis of variance, 双因素方差分析
7 Z' l# m4 |% s. vTwo-way table, 双向表$ P T; l) n% u8 k
Type I error, 一类错误/α错误2 p$ C2 b- \) Y+ e" P8 p& o& ?6 K
Type II error, 二类错误/β错误( P- _! F$ u+ W. C& k
UMVU, 方差一致最小无偏估计简称3 G3 J7 k8 z2 |$ q, l/ S
Unbiased estimate, 无偏估计5 c$ }# X# g {) y; S/ v
Unconstrained nonlinear regression , 无约束非线性回归 `5 o4 A7 W6 }0 d3 O# s! E- [
Unequal subclass number, 不等次级组含量
( @/ k, J* j- m3 m& ?Ungrouped data, 不分组资料
" B h0 V$ Y; U- \ S/ qUniform coordinate, 均匀坐标
( O+ U" q5 Y# f9 Z* ~2 G. NUniform distribution, 均匀分布
' \# J( ?$ i( y0 B0 y9 sUniformly minimum variance unbiased estimate, 方差一致最小无偏估计5 d1 I1 @4 \0 N$ t+ t
Unit, 单元; G9 S E7 {- S9 |
Unordered categories, 无序分类
* y4 o* h# X9 PUpper limit, 上限" G( h7 k0 [2 H8 h" O/ [" }
Upward rank, 升秩
5 R% L2 |# z6 o# ~Vague concept, 模糊概念- J- X# E/ E- y* z5 N
Validity, 有效性
6 e3 E# ^$ P" \# q8 [+ V/ H% @1 GVARCOMP (Variance component estimation), 方差元素估计
^% p# N3 i! j! H/ QVariability, 变异性
( p& y. M: M6 a. Q" ZVariable, 变量
: H5 ^2 V# S1 Z6 x& H( GVariance, 方差
& b: | E1 x m# FVariation, 变异5 ?* o7 {8 o0 i6 O: P; c
Varimax orthogonal rotation, 方差最大正交旋转' [+ r/ g% o( u; M
Volume of distribution, 容积0 E: f# w- V6 a R" W- k4 F7 l
W test, W检验. ?2 q- n. _; w
Weibull distribution, 威布尔分布% q0 d/ D; _! `+ z, o7 Z
Weight, 权数; j, L5 d# M% e8 O, F* b
Weighted Chi-square test, 加权卡方检验/Cochran检验8 Y6 }% Q8 R- g8 ^/ F0 c# o; O
Weighted linear regression method, 加权直线回归
* s. K8 o2 y/ ^, @! m' j* T( o& sWeighted mean, 加权平均数
& n' z0 I9 D7 Z& t) @; U3 [5 wWeighted mean square, 加权平均方差
. g1 s2 `% H. R2 h9 zWeighted sum of square, 加权平方和
! K% T h& Q+ lWeighting coefficient, 权重系数- D! u( Y& R" B* C% F- u0 [* z
Weighting method, 加权法
% U# W: X) {) Z% h Q1 zW-estimation, W估计量
4 z! l8 y0 v8 w) a& ]; s0 O3 r; w) kW-estimation of location, 位置W估计量; a/ t- o+ [* E* z- ~. u
Width, 宽度" j: ^5 J" S% n( j) s
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验3 A' o/ [" w/ ?6 \5 S+ _5 m7 r
Wild point, 野点/狂点& B- W' T7 \. e: F/ [' O% o
Wild value, 野值/狂值
! R% G( b. y f6 @Winsorized mean, 缩尾均值( Z( { c4 N0 }) l& `
Withdraw, 失访 : q- d( A& Y' T1 B' P
Youden's index, 尤登指数
5 D" S6 w: j- cZ test, Z检验
+ H5 B! |, l# x) Y" U1 z, w7 e' YZero correlation, 零相关
q% C8 A" e \" kZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
